Randomness Recoverable Secret Sharing Schemes

It is well-known that randomness is essential for secure cryptography. The randomness used in cryptographic primitives is not necessarily recoverable even by the party who can, e.g., decrypt or recover the underlying secret/message. Several cryptographic primitives that support randomness recovery have turned out useful in various applications. In this paper, we study randomness recoverable secret sharing schemes (RR-SSS), in both information-theoretic and computational settings and provide two results. First, we show that while every access structure admits a perfect RR-SSS, there are very simple access structures (e.g., in monotone AC?) that do not admit efficient perfect (or even statistical) RR-SSS. Second, we show that the existence of efficient computational RR-SSS for certain access structures in monotone AC? implies the existence of one-way functions. This stands in sharp contrast to (non-RR) SSS schemes for which no such results are known. RR-SSS plays a key role in making advanced attributed-based encryption schemes randomness recoverable, which in turn have applications in the context of designated-verifier non-interactive zero knowledge

Easing the Reuse of ML Solutions by Interactive Clustering-based Autotuning in Scientific Applications

Software is disrupting one industry after another. Currently, the automotive industry is under pressure to innovate in the area of software. New, innovative approaches to vehicles and their HW/SW architectures are required and are currently subsumed under the term “SW-defined vehicle”. However, this trend does not stop at the vehicle boundaries, but also includes communication with off-board edge and cloud services. Thinking it through further, this leads to a breakthrough technology we call “Reliable Distributed Systems”, which enables the operation of vehicles where time and safety-critical sensing and computing tasks are no longer tied to the vehicle, but can be shifted into an edge-cloud continuum. This allows a variety of novel applications and functional improvements but also has a tremendous impact on automotive HW/SW architectures and the value chain. Reliable distributed systems are not limited to automotive use cases. The ubiquitous and reliable availability of distributed computing and sensing in real-time enable novel applications and system architectures in a variety of domains: from industrial automation over building automation to consumer robotics. However, designing reliable distributed systems raises several issues and poses new challenges for edge and cloud computing stacks as well as electronic design automation

Multiscale insights into mechanical performance of a granite-based geopolymer: Unveiling the micro to macro behavior

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Information asymmetries and insider trading in firms subject to securities class action litigation: A look at managing vs. non-managing insiders

In this study, we investigate the trading patterns of corporate insiders around the announcement dates of shareholder class action lawsuits and related settlements. In particular, we explore whether these trading patterns are indicative of information asymmetries between managing and non-managing insiders. We provide evidence that litigation and settlement announcements have a significant impact on the stock prices of sued firms, and that foreknowledge of these events may be used by insiders to earn abnormal profits. We assess both actual and proposed trades by insiders in sued firms to detect abnormal trading activity prior to these events. Our results provide strong evidence of abnormal trading activity by insiders of sued firms prior to these announcements. The direction of their trades suggests the presence of informed trading prior to both litigation and settlement announcements. Moreover, we observe that managers exhibit higher abnormal trading activity than non-managing insiders prior to litigation and settlement announcements